Comment on “Genetic analysis of 16th-century whale bones prompts a revision of the impact of Basque whaling on right and bowhead whales in the western North Atlantic”
Bibliographic record
Abstract
Rastogi et al. presented their genetic analysis of 16th-century whale bones found on a Basque whaling ship excavated from Red Bay, Labrador Peninsula, Canada. Based on the results from a very small sample, these authors concluded that whaling populations were already depleted before the onset of whaling. This is in direct contradiction to historical data. They also implied that the Basques were the only Europeans whaling in the North Atlantic before the onset of Yankee whaling and that there was a belief that Basque whalers historically killed equal numbers of right and bowhead whales. Here we present data based on historical and archaeological records generated by several authors using different methodologies, which clearly show that (i) Basques were not the only whalers that impacted cetacean populations in the North Atlantic; (ii) the number of whales killed by different peoples for approximately two centuries indicates that both right and bowhead whale population levels were much higher than typically assumed; and (iii) for many years there have been records published indicating that the Basques and others killed more bowhead whales than right whales, at least in the western North Atlantic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.027 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".